商品簡介
PRACTICAL ENGINEERING STATISTICS
This lucidly written book offers engineers and advanced students all the essential statistical methods and techniques used in day-to-day engineering work. Without unnecessary digressions into formal proofs or derivations, Practical Engineering Statistics shows how to select the appropriate statistical method for a specific task and then how to apply it correctly and confidently. Clear explanations supported by real-world examples lead the reader step-by-step through each procedure. Topics covered include product design and development; estimations of the mean value and variability of measured data; comparison of processes or products; the relationships between variables; and more.
With its emphasis on practical use and its full range of engineering applications, Practical Engineering Statistics serves as an indispensable, time-saving reference for all engineers working in design, reliability, assurance, scheduling, and manufacturing.
PRACTICAL ENGINEERING STATISTICS
While engineers are frequently involved in projects that require the application of statistical methods to analysis, prediction, and planning, their background in statistics is often insufficient to the task. In many cases the engineer has had little training in statistics beyond the concepts of the mean, the standard deviation, the median, and the quartile. Even those who have had one or more courses in statistics will, at times, encounter problems which are beyond their capacity to solve or understand.
Practical Engineering Statistics is designed to give engineers the knowledge to select the statistical approach that is most appropriate to the problem at hand and the skills to confidently apply this approach to specific cases. It provides the engineer with the statistical tools needed to perform the job effectively, whether it is pro-duct design and development, estimation of the mean value and variability of measured data, comparison of processes or products, or the relationship between variables.
Its authors bring two different areas of expertise to this unique book: statistics and engineering physics. In Practical Engineering Statistics their collaboration has produced a book that clearly leads engineers step-by-step through each procedure, without time-consuming and unnecessary discussions of proofs and derivations. Statistical procedures are discussed and explained in detail and demonstrated through real-world sample problems, with correct answers always provided. Readers learn how to determine which data represent true observations and which, through human error or flawed data, are false observations.
Complex problems are presented with computer printouts of the database, intermediate steps, and results. Numerous illustrations and tables of all commonly used distributions enhance the usefulness of this invaluable book.
Virtually all engineers and advanced students, especially those in mechanical, civil, electrical, aerospace, and chemical engineering, Practical Engineering Statistics is an indispensable reference that will give them the tools to do the statistical part of their work quickly and accurately.
作者簡介
DANIEL SCHIFF is a consulting engineer and was formerly Chief Scientist of Assurance Technology Corporation. Dr. Schiff received his PhD in nuclear physics, holds six U.S. patents, and is a registered professional engineer in Massachusetts. His current work includes energy efficient design, statistical analysis, and shock and vibration analysis. He is the author of Dynamic Analysis and Failure Modes of Simple Structures, also published by Wiley.
RALPH B. D'AGOSTINO is Professor of Mathematics, Statistics, Public Health and Law at Boston University, and formerly Chairman of the Mathematics Department. In addition, Dr. D'Agostino is Director of the University's Statistics and Consulting Unit. He is an active researcher and consultant to both government and industry, a Fellow of the American Statistical Association and recipient of the Metcalf Cup and Prize for Excellence in Teaching at Boston University. He is coauthor of Factor Analysis: An Applied Approach (with E. E. Coreton) and Goodness-of-Fit Techniques (with M. A. Stephens).
目次
Statistical Inference.
Probability Models.
Descriptive Statistics.
Inferential Statistics: Mean Values.
Analysis of Proportions and Categorical Data.
Variability.
Analysis of Variance and Experimental Design I. Outliers.
Extreme Value Analysis.
Sensitivity Testing.
Regression and Correlation.
Experimental Design II.
Control Charts.
Reliability and Lifetime.
Appendix.
Bibliography.
Index.
